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Speech-to-text for AI medical scribes: Why clinical vocabulary breaks generic STT
TL;DR: Generic STT engines fail in clinical environments because language model probability overrides correct acoustic detection of medical terms, substituting phonetically plausible but clinically wrong candidates silently. The result corrupts drug names, dosages, and diagnoses before the LLM ever sees them. Before selecting an STT engine for a medical scribe, verify four things: whether vocabulary biasing works at inference time without fine-tuning, whether async diarization accurately separates clinician and patient audio, whether the model holds up on noisy consultation recordings rather than clean read-speech, and whether the vendor's data training policy covers PHI by default on your plan.
Migrating from self-hosted Whisper to a managed speech-to-text API
TL;DR: Self-hosting Whisper's true cost rarely sits in the model weights. GPU idle time, VRAM leaks under parallel load, and the engineering hours spent maintaining CUDA dependencies and diarization pipelines are where the bill compounds. For teams processing under roughly 3,000 hours per month, assuming 20% of one US FTE at $150K loaded annual cost, a managed API is cheaper, though the break-even shifts materially against your actual labor cost. Above that threshold, the decision depends on your DevOps overhead and whether audio accuracy on real-world recordings matters for downstream systems like CRM sync and coaching scores.
Migrating from AssemblyAI to Gladia: A step-by-step switching guide
TL;DR: Switching from AssemblyAI requires four concrete changes: update one auth header, remap batch endpoints, adjust the JSON response schema, and resample audio for WebSocket connections. Multiple customers independently report completing these in under a day with a rollback abstraction layer in place. The bigger structural difference is cost model: a production stack with diarization, sentiment, entities, and summarization runs $0.30/hr on AssemblyAI's Universal-2 tier because each feature is metered separately, versus a bundled base rate. This guide covers the exact parameter mappings, payload diffs, WebSocket reconfiguration, and a zero-downtime cutover strategy.
Powering virtual meetings with Speech to Text AI: Claap's success story with Gladia
Published on Jun 25, 2023
A case study showcasing the benefits of Gladia's AI API for Claap, an all-in-one video workspace that implemented our solution to provide its international users with advanced video transcription capabilities.
Meet Claap
Claap is a leading all-in-one video workspace that helps organizations speed up decision-making by reducing back-to-back virtual meetings and endless messaging threads. Claap unifies meeting recording, screen recording, and a video wiki into a single collaborative workspace, unlocking a new level of alignment, transparency, and efficiency.
Founded in France in 2021, the company serves international customers like Revolut, Kavak, and Qonto, and helps them solve their remote collaboration challenges.
• 14 employees
• 5,000+ customer workspaces
• Global user base: French, English (US/UK), Spanish, German, Dutch, Danish, Chinese, Hindi, Portuguese, Italian and other languages in use
Claap's platform with built-in transcription, powered by Gladia
Claap’s team knew that in order to realize their vision, they needed to make video content a truly intuitive medium of information. This, in turn, meant that they had to make video content easy to summarize, categorize, search, and digest. A high-quality transcription tool was therefore crucial to their roadmap.
Challenge
Claap’s Co-founder and CTO, Thomas Hernandez, needed a highly accurate, fast, and easy-to-implement multilingual solution both for core transcription and for video intelligence add-ons.
While the Claap team considered building the solution in-house using a layer of add-ons on top of an open-source product, they felt that transcription was becoming enough of a commodity that a specialized API provider would be a better fit, thanks to reduced time-to-market and lower infrastructure costs.
The issue they encountered, however, was that the incumbent providers did not meet the near-perfect quality they were looking for, as they were primarily US-centric, with lower quality for non-native English speakers. They were also either too slow, or prohibitively expensive.
Objectives
To deploy a high-quality, scalable video transcription API and audio intelligence add-ons for all Claap's customers all around the globe.
Specifications
✔️ A high-quality transcription at a scalable cost so it could be deployed in every user space.
✔️ A solution adapted to speakers from multiple geographies, with different languages and regional accents.
✔️ A transcription technology that is fast enough to add a valuable layer of insight to user videos almost immediately.
Solution
With Gladia, the Claap team was able to implement:
A highly accurate transcription solution registering a WER between 1% and 3%.
Transcription at blazing speed, with one hour of video transcribed on average in under 60s.
A truly multilingual approach to transcription, with core features and add-on all available in 99+ languages.
A quick implementation and iteration cycle, with fixes and features released every week, as well as weekly client support.
Audio intelligence features such as speaker diarization, word-level timestamps, translations, and other features, enabling Claap to make content more accessible for their international users.
Thanks to our API, Claap was able to unlock the following AI-powered functionalities for its users:
Synced playback — follow along with a video transcript while you listen to the recording;
Speaker detection — automatically detect multiple speakers to jump in the right moment;
Search within video — search the full text transcript and find the exact moment you’re looking for;
Add comments while watching transcript — easily add comments related to a specific timestamp.
Speaker diarization as seen inside Claap
Impact
After deciding to add audio transcription to their roadmap, Claap started testing the API immediately. By working with the Gladia team to iterate and scale up, they saw a noticeable impact on their own customers, from users praising the quality of the transcription to prospects converting specifically after trying it out.
In a nutshell, Claap's case study illustrates the many possibilities unlocked by audio AI for businesses, aiming to improve user experience, boost retention and upgrade its core product functionalities - all with a single turnkey API.
We're thrilled to have been part of this amazing journey, and we owe a huge thanks to our client for putting their trust in us. As we move forward, we're excited to team up with more clients, tackle new challenges, and make AI more accessible to companies worldwide.
About Gladia
Gladia provides a speech-to-text and audio intelligence API for building virtual meeting and note-taking apps, call center platforms, and media products, providing transcription, translation, and insights powered by best-in-class ASR, LLMs and GenAI models.
Having read this case study, do you feel like Gladia could be the right fit for your business too?
